Title
Optimized between-group classification: a new jackknife-based gene selection procedure for genome-wide expression data.
Abstract
A recent publication described a supervised classification method for microarray data: Between Group Analysis (BGA). This method which is based on performing multivariate ordination of groups proved to be very efficient for both classification of samples into pre-defined groups and disease class prediction of new unknown samples. Classification and prediction with BGA are classically performed using the whole set of genes and no variable selection is required. We hypothesize that an optimized selection of highly discriminating genes might improve the prediction power of BGA.We propose an optimized between-group classification (OBC) which uses a jackknife-based gene selection procedure. OBC emphasizes classification accuracy rather than feature selection. OBC is a backward optimization procedure that maximizes the percentage of between group inertia by removing the least influential genes one by one from the analysis. This selects a subset of highly discriminative genes which optimize disease class prediction. We apply OBC to four datasets and compared it to other classification methods.OBC considerably improved the classification and predictive accuracy of BGA, when assessed using independent data sets and leave-one-out cross-validation.The R code is freely available [see Additional file 1] as well as supplementary information [see Additional file 2].
Year
DOI
Venue
2005
10.1186/1471-2105-6-239
BMC Bioinformatics
Keywords
Field
DocType
algorithms,feature selection,monte carlo method,phylogeny,leave one out cross validation,variable selection,microarray data,gene expression profiling,gene selection
Genome,Jackknife resampling,Feature selection,Pattern recognition,Computer science,Multivariate statistics,Microarray analysis techniques,Artificial intelligence,Group analysis,Bioinformatics,DNA microarray,Gene expression profiling
Journal
Volume
Issue
ISSN
6
1
1471-2105
Citations 
PageRank 
References 
25
0.54
9
Authors
5
Name
Order
Citations
PageRank
Florent Baty1873.53
Michel P Bihl2250.54
Guy Perrière329240.35
Aedín C. Culhane441047.50
Martin Brutsche5873.53